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Performance Analysis of Non-stationary Peer-assisted VoD Systems Delia Ciullo 1 , Valentina Martina 1 , Michele Garetto 2 , Emilio Leonardi 1 , Gianluca Torrisi 3 1 Politecnico di Torino 2 Universit` a di Torino 3 CNR - Instituto per le


  1. Performance Analysis of Non-stationary Peer-assisted VoD Systems Delia Ciullo 1 , Valentina Martina 1 , Michele Garetto 2 , Emilio Leonardi 1 , Gianluca Torrisi 3 1 Politecnico di Torino 2 Universit` a di Torino 3 CNR - Instituto per le Applicazioni di Calcolo March 26-th, 2012 E. Leonardi Performance of P2P-VOD systems

  2. Introduction In peer-assisted Video-on-Demand (VoD) systems: E. Leonardi Performance of P2P-VOD systems

  3. Introduction In peer-assisted Video-on-Demand (VoD) systems: users browse a catalog of available videos and asynchronously issue requests to watch a given content; E. Leonardi Performance of P2P-VOD systems

  4. Introduction In peer-assisted Video-on-Demand (VoD) systems: users browse a catalog of available videos and asynchronously issue requests to watch a given content; content is divided into chunks that can be retrieved either from E. Leonardi Performance of P2P-VOD systems

  5. Introduction In peer-assisted Video-on-Demand (VoD) systems: users browse a catalog of available videos and asynchronously issue requests to watch a given content; content is divided into chunks that can be retrieved either from the servers E. Leonardi Performance of P2P-VOD systems

  6. Introduction In peer-assisted Video-on-Demand (VoD) systems: users browse a catalog of available videos and asynchronously issue requests to watch a given content; content is divided into chunks that can be retrieved either from the servers other peers currently retrieving the same video (leechers) E. Leonardi Performance of P2P-VOD systems

  7. Introduction In peer-assisted Video-on-Demand (VoD) systems: users browse a catalog of available videos and asynchronously issue requests to watch a given content; content is divided into chunks that can be retrieved either from the servers other peers currently retrieving the same video (leechers) peers storing the whole video (seeds); E. Leonardi Performance of P2P-VOD systems

  8. Introduction In peer-assisted Video-on-Demand (VoD) systems: users browse a catalog of available videos and asynchronously issue requests to watch a given content; content is divided into chunks that can be retrieved either from the servers other peers currently retrieving the same video (leechers) peers storing the whole video (seeds); chunks must be retrieved by peers almost in sequence to guarantee small play-out delays; E. Leonardi Performance of P2P-VOD systems

  9. Introduction In peer-assisted Video-on-Demand (VoD) systems: users browse a catalog of available videos and asynchronously issue requests to watch a given content; content is divided into chunks that can be retrieved either from the servers other peers currently retrieving the same video (leechers) peers storing the whole video (seeds); chunks must be retrieved by peers almost in sequence to guarantee small play-out delays; a minimum average download rate equal to the video playback rate must be sustained to guarantee service continuity; the system (exploiting servers bandwidth when needed) is able to steadily meet this constraint. E. Leonardi Performance of P2P-VOD systems

  10. Assumptions E. Leonardi Performance of P2P-VOD systems

  11. Assumptions Video is downloaded by each user at constant rate d , greater or equal to the playback rate d v ; E. Leonardi Performance of P2P-VOD systems

  12. Assumptions Video is downloaded by each user at constant rate d , greater or equal to the playback rate d v ; upload available bandwidth U i of peer i is a random variable with a assigned distribution ( U i are i.i.d.); E. Leonardi Performance of P2P-VOD systems

  13. Assumptions Video is downloaded by each user at constant rate d , greater or equal to the playback rate d v ; upload available bandwidth U i of peer i is a random variable with a assigned distribution ( U i are i.i.d.); users contribute their upload bandwidth to the video distribution as long as they are in the system; E. Leonardi Performance of P2P-VOD systems

  14. Assumptions Video is downloaded by each user at constant rate d , greater or equal to the playback rate d v ; upload available bandwidth U i of peer i is a random variable with a assigned distribution ( U i are i.i.d.); users contribute their upload bandwidth to the video distribution as long as they are in the system; the arrival process of requests (and users) for a video is a (possibly non-homogeneous) Poisson process with intensity λ ( t ); E. Leonardi Performance of P2P-VOD systems

  15. Assumptions Video is downloaded by each user at constant rate d , greater or equal to the playback rate d v ; upload available bandwidth U i of peer i is a random variable with a assigned distribution ( U i are i.i.d.); users contribute their upload bandwidth to the video distribution as long as they are in the system; the arrival process of requests (and users) for a video is a (possibly non-homogeneous) Poisson process with intensity λ ( t ); user’s sojourn time is described by an arbitrary random variable T with finite mean T and complementary cumulative distribution function G T ( x ). E. Leonardi Performance of P2P-VOD systems

  16. Preliminary Observations The number of active users N ( t ) follows a Poisson distribution with mean � ∞ N ( t ) = λ ( t − x ) G T ( x ) d x ; 0 E. Leonardi Performance of P2P-VOD systems

  17. Preliminary Observations The number of active users N ( t ) follows a Poisson distribution with mean � ∞ N ( t ) = λ ( t − x ) G T ( x ) d x ; 0 τ d = L / d is the time needed to download the whole video, and � τ d T d = 0 G T ( x ) dx is the average time spent by peers downloading the video, taking into account premature abandonments; E. Leonardi Performance of P2P-VOD systems

  18. Preliminary Observations The number of active users N ( t ) follows a Poisson distribution with mean � ∞ N ( t ) = λ ( t − x ) G T ( x ) d x ; 0 τ d = L / d is the time needed to download the whole video, and � τ d T d = 0 G T ( x ) dx is the average time spent by peers downloading the video, taking into account premature abandonments; N d ( t ) is the number of downloading users with mean � τ d N d ( t ) = 0 λ ( t − x ) G T ( x ) d x , and N seed ( t ) the number of seeds with mean N seed ( t ) = N ( t ) − N d ( t ); E. Leonardi Performance of P2P-VOD systems

  19. Preliminary Observations The number of active users N ( t ) follows a Poisson distribution with mean � ∞ N ( t ) = λ ( t − x ) G T ( x ) d x ; 0 τ d = L / d is the time needed to download the whole video, and � τ d T d = 0 G T ( x ) dx is the average time spent by peers downloading the video, taking into account premature abandonments; N d ( t ) is the number of downloading users with mean � τ d N d ( t ) = 0 λ ( t − x ) G T ( x ) d x , and N seed ( t ) the number of seeds with mean N seed ( t ) = N ( t ) − N d ( t ); we define the average system load as: γ = dT d U T . E. Leonardi Performance of P2P-VOD systems

  20. Goal Our goal is: [1] D.Ciullo, V.Martina, M.Garetto, E.Leonardi, G.L.Torrisi, “Stochastic Analysis of Self-Sustainability in Peer-Assisted VoD Systems”, Session TS05, Thursday, h. 8.30-10.00 E. Leonardi Performance of P2P-VOD systems

  21. Goal Our goal is: to characterize the bandwidth requested from the servers S (and its average S ); [1] D.Ciullo, V.Martina, M.Garetto, E.Leonardi, G.L.Torrisi, “Stochastic Analysis of Self-Sustainability in Peer-Assisted VoD Systems”, Session TS05, Thursday, h. 8.30-10.00 E. Leonardi Performance of P2P-VOD systems

  22. Goal Our goal is: to characterize the bandwidth requested from the servers S (and its average S ); we develop an approximate efficient and accurate fluid model to compute S ; [1] D.Ciullo, V.Martina, M.Garetto, E.Leonardi, G.L.Torrisi, “Stochastic Analysis of Self-Sustainability in Peer-Assisted VoD Systems”, Session TS05, Thursday, h. 8.30-10.00 E. Leonardi Performance of P2P-VOD systems

  23. Goal Our goal is: to characterize the bandwidth requested from the servers S (and its average S ); we develop an approximate efficient and accurate fluid model to compute S ; our approach is able to capture several stochastic effects related to peer churn, upload bandwidth heterogeneity, non-stationary traffic conditions; [1] D.Ciullo, V.Martina, M.Garetto, E.Leonardi, G.L.Torrisi, “Stochastic Analysis of Self-Sustainability in Peer-Assisted VoD Systems”, Session TS05, Thursday, h. 8.30-10.00 E. Leonardi Performance of P2P-VOD systems

  24. Goal Our goal is: to characterize the bandwidth requested from the servers S (and its average S ); we develop an approximate efficient and accurate fluid model to compute S ; our approach is able to capture several stochastic effects related to peer churn, upload bandwidth heterogeneity, non-stationary traffic conditions; our methodology can be exploited to design efficient peer-assisted VoD systems and optimal resource allocation strategies. [1] D.Ciullo, V.Martina, M.Garetto, E.Leonardi, G.L.Torrisi, “Stochastic Analysis of Self-Sustainability in Peer-Assisted VoD Systems”, Session TS05, Thursday, h. 8.30-10.00 E. Leonardi Performance of P2P-VOD systems

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